ArticleCancer medicine2024
Developing Individualized Follow-Up Strategies Based on High-Risk Recurrence Factors and Dynamic Risk Assessment for Locally Advanced Rectal Cancer.
Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- ASO Author Reflections: Decoding Conditional Risks of Recurrence in Appendix Cancer to Guide Post-Treatment Surveillance.Annals of surgical oncology · 2026Article
- Interpretable machine learning model for predicting 5-Year postoperative recurrence risk in patients with stage III colon cancer using preoperative laboratory tests: a two-centre study.BMC gastroenterology · 2026Article
- Article
- Development and internal validation of a clinical prediction model for 1-year recurrence after first-ever ischemic stroke.Frontiers in neurology · 2026Article
- Temporal dynamics and determinants of early recurrence after curative resection for stage I-III rectal cancer: integrated analyses of hazard function, survival, and competing risks.Frontiers in oncology · 2026Article
- Article
- Pan-Immune-Inflammation Value (PIV) and Prognostic Nutritional Index (PNI) are Associated with Distant Metastasis in Colorectal Cancer withInternational journal of general medicine · 2025Article
- Histopathological Analysis of Lipopolysaccharide-Induced Liver Inflammation and Thrombus Formation in Mice: The Protective Effects of Aspirin.Current issues in molecular biology · 2024Article
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Authors and funding
6 authors.
Funding
Abstract
backgroundLocally advanced rectal cancer (LARC) is one of the most common malignant tumors worldwide, and its incidence is increasing year by year. Despite multimodal treatment, the recurrence rate of LARC patients remains high, about 20%-50%. However, the follow-up strategy according to tumor stage has certain limitations. There is no consensus on the optimal frequency and duration of follow-up. This study aims to comprehensively analyze the high-risk factors for recurrence in LARC from clinical characteristics, nutritional indicators, and imaging indexes. It intends to utilize conditional survival (CS) evaluation to assess dynamic survival and recurrence risks after comprehensive treatment of LARC and to develop individualized follow-up strategies.
methodsLogistic regression was utilized to analyze the independent recurrence factors in LARC patients. Calibration curve, decision curve, and ROC curve were employed to evaluate the model's efficacy. Kaplan-Meier curve was used to calculate CS rate and compare survival differences among different risk groups.
resultsA total of 561 patients were analyzed in our study. Our multivariable logistic regression analysis revealed that the prognostic nutritional index (PNI), extramural vascular invasion (EMVI), vascular tumor thrombus, perineural invasion, and tumor size were independent factors for recurrence. Subsequently, a nomogram model was constructed and risk stratification was performed. Calibration curves and decision curves demonstrated that the model exhibited good clinical efficacy. The area under the ROC curve for the model was 0.763, indicating good sensitivity and specificity. Kaplan-Meier curves showed significant differences in survival among different risk groups. Furthermore, we observed that the CS without local recurrence and distant metastasis increased each year, while the cumulative recurrence risk decreased annually with prolonged survival time. Tailored follow-up intensities were developed for different risk groups and clinical stages based on the cumulative recurrence risk.
conclusionThe personalized follow-up strategy based on risk stratification can optimize resource allocation, early detection of recurrence or metastasis, and ultimately enhance the overall care and prognosis of LARC patients.
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